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Record W2552589662 · doi:10.1109/piers.2016.7734461

On-chip optical pulse shaping using cascaded co-directional couplers

2016· article· en· W2552589662 on OpenAlexaff
Hamed Pishvai Bazargani, José Azaña

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsReconfigurabilityApodizationWaveguideComputer scienceUltrashort pulseOpticsPulse shapingGratingOptical switchChipElectronic engineeringDiffraction gratingPhysicsTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Summary form only given. Picosecond-resolution optical pulse shaping (OPS) is desired for many important applications in ultrahigh-bit-rate optical fiber communications and ultrafast optical signal processing. Commercially available optical pulse shapers operate based on the well-established spatial-domain processing approach, allowing programmable synthesis of arbitrary waveforms with resolutions better than 100 fs. However, the need for high-quality bulk-optics components makes the implementation of this method relatively complex. Similar OPS principles have been implemented using compact on-chip arrayed diffraction gratings (ADGs), but ADGs are challenging to fabricate, yet they suffer from limited spectral resolution. All-fiber and integrated-waveguide grating structures have been considered as another solution for OPS due to their mature fabrication process and low loss (particularly in fiber-based schemes). However, grating devices have proven challenging to fabricate in integrated-waveguide configurations and it would be also difficult to add reconfigurability in these structures. To overcome the aforementioned limitations, we will review here recent work on a novel design based on a structure of cascaded co-directional couplers. In particular, our new design exploits the fact that under relatively weak-coupling conditions, the `discrete' amplitude and phase `apodization' profile of the structure can be directly mapped into the output temporal response of the device, see scheme in Fig. 1. We refer to this approach as discrete space-to-time mapping (D-STM). The proposed design is based on forward coupling between a main-waveguide and a bus-waveguide, where the coupling is controlled in a discrete fashion through standard co-directional couplers (`amplitude apodization'). On the other hand, phase tuning can be done by adjusting the relative path-length different between sections of bus and main-waveguide at each stage of the device. The devices obtained through this new design method are notably simpler to fabricate than their Bragg grating-based counterparts, while potentially enabling reconfigurability through well-established mechanisms. Using D-STM, we have successfully re-shaped (sub-)picosecond Gaussian-like pulses into several practically relevant pulse shapes, including a 1.25 ps (FWHM) long flat-top pulse, an 8-bit, 200 G-baud 16-quadrature amplitude modulation (QAM) bit sequence and a 70 ps (FW) long high quality flat-top pulse. The power spectral responses (PSRs) presented in Fig. 2, have been measured using an optical vector analyzer (O-VA). Besides, direct time-domain characterization of the output synthesized waveforms has been carried out using Fourier-transform spectral interferometry (FTSI). As shown in Fig. 2(f) a combination of single-mode waveguide (SMW) and multi-mode waveguide (MMW) has been used to reduce the loss and phase-noise for the case of long-duration OPS devices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.266
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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